Multi-sensor monitoring systems can include a central computing device and various peripheral sensors. The central computing device can act as a data aggregator for the peripheral sensors. Conventional multi-sensor monitoring systems can require significant user setup. For example, a user may need to connect the central computing device and each peripheral sensor to a network, and manually pair each peripheral sensor to the central computing device over the network. This process can be burdensome to users in demographics that are not technologically savvy. Conversely, some multi-sensor monitoring systems may have a streamlined pairing workflow that is hard-coded to pair a specific set of peripheral sensors to the central computing device. However, hard-coding can result in an inflexible sensor combination that cannot be dynamically changed across multiple users of the multi-sensor monitoring system. Changes to a hard-coded system can require full code recompilations and new application releases for each user, which can make it difficult to scale the multi-sensor monitoring system.
Multi-sensor monitoring systems can include health sensor systems. Many health sensor systems may not transform collected data into health outcomes for patients. Health sensor systems that use remote monitoring technology may rely on human interpretation of health sensor data, or they may manually inject health sensor data from many vertically integrated sensor systems (e.g., distinct oxygen sensing and glucose sensing systems) into a separate third-party analytics provider. Afterwards, the health sensor systems may then provide the output of these analytics to service providers (e.g., emergency response services, therapeutics companies, etc.). Currently, no system exists that agnostically connects health sensor systems to analytics that detect patient deteriorations and interventional services that address such deteriorations. Furthermore, no system performs the aforementioned steps in a continuous loop to iterate upon its automated decision making processes. The lack of such a system introduces labor inefficiencies and translational costs for today's medical providers.